Principal Scientist, Generative AI
AstraZeneca2 hours ago
Beijing, ChinaStaff+
Responsibilities
- Collaborate with scientists across drug development to understand challenges and build platforms supporting their research.
- Build generative AI prototypes that accelerate routine scientific processes and demonstrate business value.
- Design and deploy machine learning models for large-scale clinical transcriptomics, proteomics, and cell painting analysis.
- Design agentic AI workflows integrating bioinformatics and machine learning analysis steps.
- Calculate project ROI and impact using information and assumptions gathered from stakeholders and future users.
- Provide strategic direction for generative AI adoption and help define and implement the organization’s generative AI strategy.
- Ensure infrastructure and platforms support scaling exploratory research into production solutions.
- Manage stakeholder relationships, communicate results and uncertainties clearly, and drive utilization of information resources and services.
- Improve machine learning development environments, platforms, and tooling.
- Coordinate with global AI research teams across China, India, Europe, and the US East Coast.
- Collaborate with cybersecurity, data privacy, governance, and compliance functions to secure computing environments while supporting productivity.
Requirements
- Bachelor’s or master’s degree, or equivalent years of experience, in mathematics, computer science, engineering, physics, statistics, computational sciences, or a related field.
- Advanced Python programming and experience with AI libraries and frameworks such as TensorFlow and PyTorch.
- Proven experience in AI and machine learning, including areas such as deep learning, natural language processing, computer vision, and reinforcement learning.
- Experience with prompt engineering, Retrieval-Augmented Generation, and LLM fine-tuning.
- Experience implementing generative AI workflows using large language models, foundation models, or agentic frameworks, ideally in pharma or healthcare.
- Experience analyzing large, high-dimensional, unstructured datasets and communicating conclusions and recommended actions to stakeholders.
- Experience designing agentic AI workflows and planning strategically for AI needs in a large organization.
- Strong knowledge of software development and machine learning deployment principles.
- Familiarity with CNNs, vision transformers, diffusion models, ResNet, UNet, DINO, CLIP, and Stable Diffusion.
- Familiarity with GitHub, CI/CD pipelines, DevOps, and MLOps practices.
- Demonstrable experience with AWS or a similar cloud environment.
- Experience with Kubernetes and container-based application deployments.
- Excellent communication and presentation skills for explaining complex AI concepts to non-technical partners.
- Strong leadership and project management skills with a record of leading successful AI projects.
- Knowledge of AI ethics and responsible AI practices.
- Experience in life sciences, healthcare, or pharmaceuticals is desirable.
- Experience working in a complex global organization is desirable.
- Experience with LLM frameworks such as LangChain, AutoGen, and LlamaIndex is desirable.
- Experience with foundation models for transcriptomics or Cell Painting data, such as Geneformer, scGPT, and scFoundation, is desirable.
- Publications in top AI conferences or journals such as NeurIPS, ICML, Nature Machine Intelligence, Nature Communications, or NEJM AI are desirable.
Tech Stack
Categories
Forward Deployed
About AstraZeneca
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